[Help-glpk] Free linear programing course on Coursera

[Harley]

As someone who never did a college level linear programming course, I have enrolled in the following free course on Coursera for the Linear and Discrete Optimization course that is to start on Feb 18:

   https://www.coursera.org/course/linearopt

I have included the details if there are others on the GLPK list who are interested in doing the course or passing on the details.

Regards,

Harley

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Linear and Discrete Optimization
Friedrich Eisenbrand

The course is an introduction to linear and discrete optimization - an important part of computational mathematics with a wide range of applications in many areas of everyday life.

Next Session:
Feb 18th 2013 (7 weeks long)
Workload: 4-6 hours/week

About the Course

This course serves as an introduction to linear and discrete optimization from the viewpoint of a mathematician or computer scientist.  Besides learning how linear and discrete optimization can be applied, we focus on understanding methods that solve linear programs and discrete optimization problems in a mathematically rigorous way.

We will answer  questions like:

    Does a particular method work correctly?
    Does it terminate and, if yes, in what time?
    Can we prove that a solution is optimal?

The course starts by discussing what a linear program is and how linear programming can be applied. Then, we will treat the simplex method and the theory of duality. We will also discuss integer programming problems where the variables are constrained to integer values. Finally we will address the question of whether linear programs can be efficiently solved in theory which leads us to the ellipsoid method.

The course constitutes about half of the material on linear and discrete optimization that is taught for mathematics and computer science undergraduates at EPFL and will feature video lectures, quizzes, programming assignments, and a final exam.

About the Instructor(s)

Friedrich Eisenbrand is a professor of mathematics and (by courtesy) computer science at EPFL. His main research interests lie in the field of discrete optimization, in particular in algorithms and complexity, integer programming, geometry of numbers, and applied optimization. He is best known for his work on efficient algorithms for integer programming in fixed dimension and the theory of cutting planes, which are an important tool to solve large scale industrial optimization problems.

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